Post Similarity search using vector databases #2261
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Nice article, I spotted a few typos here and there, HTH.
| With LLMs becoming increasingly popular we often see them being used even for tasks that are not directly related to text generation. | ||
| Such case is using LLMs for recommendation systems. In this post we'll see how you can build such a system using https://docs.quarkiverse.io/quarkus-langchain4j/dev/index.html[Quarkus Langchain4j] | ||
| but without using LLMs. More specifically we'll create a simple movie similarity search system using a vector database. The role | ||
| of https://docs.quarkiverse.io/quarkus-langchain4j/dev/index.html[Quarkus Langchain4j] in this store is to abstract the underlying vector database through the `EmbeddingStore` interface. |
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Wasn't sure what you wanted to write but store looked odd?
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| of https://docs.quarkiverse.io/quarkus-langchain4j/dev/index.html[Quarkus Langchain4j] in this store is to abstract the underlying vector database through the `EmbeddingStore` interface. | |
| of https://docs.quarkiverse.io/quarkus-langchain4j/dev/index.html[Quarkus Langchain4j] in this story is to abstract the underlying vector database through the `EmbeddingStore` interface. |
| but without using LLMs. More specifically we'll create a simple movie similarity search system using a vector database. The role | ||
| of https://docs.quarkiverse.io/quarkus-langchain4j/dev/index.html[Quarkus Langchain4j] in this store is to abstract the underlying vector database through the `EmbeddingStore` interface. | ||
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| A relevant sample has been recently added to the https://github.com/quarkiverse/quarkus-langchain4j/tree/main/samples/[Quarkus Langchain4j samples]. |
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Could you fix LangChain4j case everywhere?
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| To be able to use these dependencies without needing to specify versions, the bom can be add imported to the `dependencyManagement` of the project: |
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| To be able to use these dependencies without needing to specify versions, the bom can be add imported to the `dependencyManagement` of the project: | |
| To be able to use these dependencies without needing to specify versions, the bom can be added to the `dependencyManagement` of the project: |
| </dependency> | ||
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| To properly use the in process embedding model we need to configure it in the `application.properties` file. |
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| To properly use the in process embedding model we need to configure it in the `application.properties` file. | |
| To properly use the in-process embedding model we need to configure it in the `application.properties` file. |
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| To properly use the in process embedding model we need to configure it in the `application.properties` file. | ||
| We also need to configure the pgvector dimension an ensure it's aligned with the dimension of the embedding model. |
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| We also need to configure the pgvector dimension an ensure it's aligned with the dimension of the embedding model. | |
| We also need to configure the pgvector dimension and ensure it's aligned with the dimension of the embedding model. |
| } | ||
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| To use the CSV mapper, we'll need to `jackson` csv dataformat: |
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| To use the CSV mapper, we'll need to `jackson` csv dataformat: | |
| To use the CSV mapper, we'll need to add Jackson's CSV dataformat dependency: |
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| ==== Bringing it all together ==== | ||
| The only thing that's left is to create a REST endpoint that will allow us to search for similar movies. We could also use a simple UI. | ||
| Let's start with the REST endpoint. It's pretty straight forward. We need to methods one for movie searching and one for searching similar movies. |
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| Let's start with the REST endpoint. It's pretty straight forward. We need to methods one for movie searching and one for searching similar movies. | |
| Let's start with the REST endpoint. It's pretty straightforward. We need two methods, one for searching movies and one for searching similar movies. |
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| The key elements of that page are: | ||
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| * movie-box: a text filed for entering the movie title |
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| * movie-box: a text filed for entering the movie title | |
| * movie-box: a text field for entering the movie title |
| * movie-poster: an image for displaying the movie poster | ||
| * similar-results: an additional unordered list for displaying the similar movies | ||
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| It's important to remember that the `Movie` entity is using `jackson` to map the CSV columns to the entity fields. |
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| It's important to remember that the `Movie` entity is using `jackson` to map the CSV columns to the entity fields. | |
| It's important to remember that the `Movie` entity is using Jackson to map the CSV columns to the entity fields. |
| </html> | ||
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| I won't go into much detail about the hmtl code as it's outside the scope of this post. |
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| I won't go into much detail about the hmtl code as it's outside the scope of this post. | |
| I won't go into much detail about the HTML code as it's outside the scope of this post. |
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This is a post on how to use quarkus with vector databases to implement a similarity search example.